class_docstr: Modifies all input metrics of the specified metric to have the given filter.
  
  This is useful for programmatically generating different manifests to create different test cases.
code: def transform_model(
      self, semantic_manifest: PydanticSemanticManifest
  ) -> PydanticSemanticManifest:
      input_metrics = []
  
      for metric in semantic_manifest.metrics:
          if (
              MetricReference(element_name=metric.name)
              != self._metric_reference
          ):
              continue
          for input_metric in metric.input_metrics:
              input_metric.filter = self._where_filter_intersection
              input_metrics.append(input_metric)
  
      if len(input_metrics) == 0:
          raise RuntimeError("Did not update any input metrics.")
  
      return semantic_manifest
  
file_path: metricflow/metricflow/test/model/modify/modify_input_metric_filter.py
imports: from __future__ import annotations
  import logging
  from dbt_semantic_interfaces.implementations.filters.where_filter import PydanticWhereFilterIntersection
  from dbt_semantic_interfaces.implementations.semantic_manifest import PydanticSemanticManifest
  from dbt_semantic_interfaces.references import MetricReference
  from dbt_semantic_interfaces.transformations.transform_rule import SemanticManifestTransformRule
  from typing_extensions import override
label_desc: Use image node_id 2 for calling the ModifyInputMetricFilterTransform obj's underlying member method code with example usage: obj.transform_model(semantic_manifest) and returns: semantic_manifest